Temat: alkane - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Homogeneous catalytic systems for selective oxidation of methane: state of the art
Autorzy:: Balcer, S.
Powiązania:: https://bibliotekanauki.pl/articles/777855.pdf
Data publikacji:: 2015
Wydawca:: Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
Tematy:: alkane functionalization
methane
methanol
catalytic systems
homogeneous catalytic systems
Opis:: Homogeneous catalysts for methane oxidation are of a particular interest from scientific and economic points of view. The results show a great potential for activation and functionalization of CH bonds of unreactive methane. There are still gaps in the knowledge of how to rationally design catalysts for this process. In this paper state-of-the-art. in methane oxidation homogenous catalysis is presented.
Źródło:: Polish Journal of Chemical Technology; 2015, 17, 3; 52-61
1509-8117
1899-4741
Pojawia się w:: Polish Journal of Chemical Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Laminar burning velocity predictions of single-fuel mixtures of C1-C7 normal hydrocarbon and air
Autorzy:: Jach, A.
Żbikowski, M.
Teodorczyk, A.
Powiązania:: https://bibliotekanauki.pl/articles/243965.pdf
Data publikacji:: 2018
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: laminar burning velocity
hydrocarbon
machine learning
LOGEsoft
alkane
MATLAB
Opis:: The numerical modelling of combustion phenomena is an important task due to safety issues and development and optimization of engines. Laminar burning velocity (LBV) is one of the most important physical properties of a flammable mixture. Knowing its exact value if crucial for assessment of flame stabilization, turbulent flame structure. It influences strongly safety, probability of knocking combustion and it is one of parameters used for assessment and development of detailed chemical kinetic mechanisms. Hence, the goal of this work is to develop models by means of Machine Learning algorithms for predicting laminar burning velocities of single-fuel C1-C7 normal hydrocarbon and air mixtures. Development of the models is based on a large experimental data set collected from literature. In total more than 1000, LBVs were accumulated for hydrocarbons from methane up to n-heptane. The models are developed in MATLAB 2018a with use of Machine Learning toolbox. Algorithms taken into account are multivariate regression, support vector machine, and artificial neural network. Performance of the models is compared with most widely used detailed chemical kinetics mechanisms’ predictions obtained with use of LOFEsoft. These kind of models might be efficiently used in CFD combustion models based on flamelet approach. The main advantage in comparison to chemical kinetics calculation is much shorter computational time needed for computations of a single value and comparable performance in terms of R2 (coefficient of determination), RMSE (root-mean-square error) and MAE (mean absolute error).
Źródło:: Journal of KONES; 2018, 25, 3; 227-235
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

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